AI Reliability by Design.
Verify AI outputs against your trusted facts before they reach enterprise applications—with a deterministic release gate and inspection records you can verify offline.
7-scene guided walkthrough
0 Model Calls
Gateway verification mode
76 Test Suites / 1,655 Checks
Automated, on every change
Fail-Closed by Design
Deterministic gate, not model opinion
Hosted on Vercel
Air-gapped deployment on roadmap
Interactive Demo
Recorded demonstration mode on fictional ground truth. Switch tabs to explore each shipped workflow.
A customer AI or RAG system generated an answer. ModelFusion checks it against customer ground truth with 0 model calls.
Supplied Fact Sheet
External answer
"Data processed exclusively in the United States."QUARANTINED — NOT RELEASED
Conflict detected on Data Residency (Expected: Canada, Received: United States). Answer withheld; 0 model calls made.
Pre-recorded outcome from Slice 9 (PR #71). Not a live system response.
Architecture
Four combinations plus a section-scoring module are in production. The configurable builder is next.
Verify existing AI/RAG answers before application release. 0 model calls, deterministic rule evaluation, no generative step in the check.
Multi-model generation (Haiku 5.5, DeepSeek V4.1 Flash, GPT-6.1 Sol) with non-text active screening by TypeSafe Jev, discarding conflicting drafts before synthesis.
Proposer panel with structured meta-judge analysis across 5 dimensions: Consensus, Contradictions, Partial Coverage, Unique Insights, Blind Spots.
Every release or withhold produces a downloadable, hash-bound record with citations to the supplied ground truth.
Inside Fusion Playground, TypeSafe Jev scores each analysis section before synthesis. Agreement score mode compares each section with the other models’ drafts. Evidence mode compares each section with evidence you supply. Only sections scoring 0.90 or higher go into the fused answer. Scores are advisory and don’t trigger the release gate.
Native visual builder canvas where nodes connect left-to-right and the audit gate is locked and cannot be bypassed, plus the JevEval candidate eval module to visually wire custom high-risk workflows.
The Seam
Pluggable model adapters propose. A non-text filter screens. A deterministic gate decides.
Invariant Rule
The audit stage is mandatory. No model module can release an answer on its own; the deterministic gate is the sole release authority.
Compounding Flywheel
Pillar 1
Scouts each new model, graph technique, or ontology and maps where it plugs in.
Pillar 2
Codex and AI reviewers ship each feature with tests, independent review, and release records (76 Jest suites, 1,655 tests).
Pillar 3
Fits ModelFusion to client sources, leaving behind reusable enterprise adapters (ERP, SharePoint, Confluence).
Pillar 4
Packages verified adapters into the commercial framework.
The four pillars run clockwise: 1 feeds 2, 2 feeds 3, 3 feeds 4, and 4 feeds back into 1.
Integrations & Ecosystem
Running in real Telegram bot workflows today, integrated with Hermes Agent and OpenClaw for first-tier testing.
Pluggable OpenRouter adapter today. First design-partner connector partnership (SharePoint or Confluence candidate) on roadmap.
Private vLLM and Ollama inference, plus VPC and air-gapped deployments, are on the roadmap. Hosted on Vercel today.
Founder
Founder & AI Product Architect
Building ModelFusion™ to make multi-model AI verification the default for high-stakes, production workflows.
FAQ
Questions? getaccess@modelfusion.ai